Database System Concepts, 5th Ed.

©Silberschatz, Korth and Sudarshan

See www.db-book.com for conditions on re-use

Chapter 3: SQL

©Silberschatz, Korth and Sudarshan3.2Database System Concepts, 5th Edition, Oct 5, 2006

Chapter 3: SQL

Data Definition

Basic Query Structure

Set Operations

Aggregate Functions

Null Values

Nested Subqueries

Complex Queries

Views

Modification of the Database

Joined Relations**

©Silberschatz, Korth and Sudarshan3.3Database System Concepts, 5th Edition, Oct 5, 2006

History

IBM Sequel language developed as part of System R project at the

IBM San Jose Research Laboratory

Renamed Structured Query Language (SQL)

ANSI and ISO standard SQL:

zSQL-86

zSQL-89

zSQL-92

zSQL:1999 (language name became Y2K compliant!)

zSQL:2003

Commercial systems offer most, if not all, SQL-92 features, plus

varying feature sets from later standards and special proprietary

features.

zNot all examples here may work on your particular system.

©Silberschatz, Korth and Sudarshan3.4Database System Concepts, 5th Edition, Oct 5, 2006

Data Definition Language

The schema for each relation.

The domain of values associated with each attribute.

Integrity constraints

The set of indices to be maintained for each relations.

Security and authorization information for each relation.

The physical storage structure of each relation on disk.

Allows the specification of not only a set of relations but also

information about each relation, including:

©Silberschatz, Korth and Sudarshan3.5Database System Concepts, 5th Edition, Oct 5, 2006

Domain Types in SQL

char(n). Fixed length character string, with user-specified length n.

varchar(n). Variable length character strings, with user-specified maximum

length n.

int. Integer (a finite subset of the integers that is machine-dependent).

smallint. Small integer (a machine-dependent subset of the integer

domain type).

numeric(p,d). Fixed point number, with user-specified precision of pdigits,

with ndigits to the right of decimal point.

real, double precision. Floating point and double-precision floating point

numbers, with machine-dependent precision.

float(n). Floating point number, with user-specified precision of at least n

digits.

More are covered in Chapter 4.

©Silberschatz, Korth and Sudarshan3.6Database System Concepts, 5th Edition, Oct 5, 2006

Create Table Construct

An SQL relation is defined using the create table command:

create table r (A1D1, A2D2, ..., AnDn,

(integrity-constraint1),

...,

(integrity-constraintk))

zris the name of the relation

zeach Aiis an attribute name in the schema of relation r

zDiis the data type of values in the domain of attribute Ai

Example:

create table branch

(branch_name char(15) not null,

branch_city char(30),

assets integer)

©Silberschatz, Korth and Sudarshan3.7Database System Concepts, 5th Edition, Oct 5, 2006

Integrity Constraints in Create Table

not null

primary key (A1, ..., An )

Example: Declare branch_name as the primary key for branch

.create table branch

(branch_name char(15),

branch_city char(30),

assets integer,

primary key (branch_name))

primary key declaration on an attribute automatically ensures

not null in SQL-92 onwards, needs to be explicitly stated in

SQL-89

©Silberschatz, Korth and Sudarshan3.8Database System Concepts, 5th Edition, Oct 5, 2006

Drop and Alter Table Constructs

The drop table command deletes all information about the dropped

relation from the database.

The alter table command is used to add attributes to an existing

relation:

alter table r add A D

where Ais the name of the attribute to be added to relation r and D

is the domain of A.

zAll tuples in the relation are assigned null as the value for the

new attribute.

The alter table command can also be used to drop attributes of a

relation:

alter table rdrop A

where Ais the name of an attribute of relation r

zDropping of attributes not supported by many databases

©Silberschatz, Korth and Sudarshan3.9Database System Concepts, 5th Edition, Oct 5, 2006

Basic Query Structure

SQL is based on set and relational operations with certain

modifications and enhancements

A typical SQL query has the form:

select A1, A2, ..., An

from r1, r2, ..., rm

where P

zAi represents an attribute

zRirepresents a relation

zPis a predicate.

This query is equivalent to the relational algebra expression.

The result of an SQL query is a relation.

))(( 21,,, 21 mPAAA rrr

n×

∏K

©Silberschatz, Korth and Sudarshan3.10Database System Concepts, 5th Edition, Oct 5, 2006

The select Clause

The select clause list the attributes desired in the result of a query

zcorresponds to the projection operation of the relational algebra

Example: find the names of all branches in the loan relation:

select branch_name

from loan

In the relational algebra, the query would be:

∏branch_name (loan)

NOTE: SQL names are case insensitive (i.e., you may use upper- or

lower-case letters.)

zE.g. Branch_Name ≡BRANCH_NAME ≡branch_name

zSome people use upper case wherever we use bold font.

©Silberschatz, Korth and Sudarshan3.11Database System Concepts, 5th Edition, Oct 5, 2006

The select Clause (Cont.)

SQL allows duplicates in relations as well as in query results.

To force the elimination of duplicates, insert the keyword distinct after

select.

Find the names of all branches in the loan relations, and remove

duplicates

select distinct branch_name

from loan

The keyword all specifies that duplicates not be removed.

select all branch_name

from loan

©Silberschatz, Korth and Sudarshan3.12Database System Concepts, 5th Edition, Oct 5, 2006

The select Clause (Cont.)

An asterisk in the select clause denotes “all attributes”

select *

from loan

The select clause can contain arithmetic expressions involving the

operation, +, –, ∗, and /, and operating on constants or attributes of

tuples.

The query:

select loan_number, branch_name, amount ∗100

from loan

would return a relation that is the same as the loan relation, except that

the value of the attribute amount is multiplied by 100.

©Silberschatz, Korth and Sudarshan3.13Database System Concepts, 5th Edition, Oct 5, 2006

The where Clause

The where clause specifies conditions that the result must satisfy

zCorresponds to the selection predicate of the relational algebra.

To find all loan number for loans made at the Perryridge branch with

loan amounts greater than $1200.

select loan_number

from loan

where branch_name = 'Perryridge' and amount > 1200

Comparison results can be combined using the logical connectives and,

or, and not.

Comparisons can be applied to results of arithmetic expressions.

©Silberschatz, Korth and Sudarshan3.14Database System Concepts, 5th Edition, Oct 5, 2006

The where Clause (Cont.)

SQL includes a between comparison operator

Example: Find the loan number of those loans with loan amounts between

$90,000 and $100,000 (that is, ≥$90,000 and ≤$100,000)

select loan_number

from loan

where amount between 90000 and 100000

©Silberschatz, Korth and Sudarshan3.15Database System Concepts, 5th Edition, Oct 5, 2006

The from Clause

The from clause lists the relations involved in the query

zCorresponds to the Cartesian product operation of the relational algebra.

Find the Cartesian product borrower X loan

select ∗

from borrower, loan

Find the name, loan number and loan amount of all customers

having a loan at the Perryridge branch.

select customer_name, borrower.loan_number, amount

from borrower, loan

where borrower.loan_number = loan.loan_number and

branch_name = 'Perryridge'

©Silberschatz, Korth and Sudarshan3.16Database System Concepts, 5th Edition, Oct 5, 2006

The Rename Operation

The SQL allows renaming relations and attributes using the as clause:

old-name as new-name

Find the name, loan number and loan amount of all customers; rename the

column name loan_number as loan_id.

select customer_name, borrower.loan_number as loan_id, amount

from borrower, loan

where borrower.loan_number = loan.loan_number

©Silberschatz, Korth and Sudarshan3.17Database System Concepts, 5th Edition, Oct 5, 2006

Tuple Variables

Tuple variables are defined in the from clause via the use of the as

clause.

Find the customer names and their loan numbers for all customers

having a loan at some branch.

Find the names of all branches that have greater assets than

some branch located in Brooklyn.

select distinct T.branch_name

from branch as T, branch as S

where T.assets > S.assets and S.branch_city = 'Brooklyn'

Keyword as is optional and may be omitted

borrower as T ≡borrower T

select customer_name, T.loan_number, S.amount

from borrower as T, loan as S

where T.loan_number = S.loan_number

©Silberschatz, Korth and Sudarshan3.18Database System Concepts, 5th Edition, Oct 5, 2006

String Operations

SQL includes a string-matching operator for comparisons on character

strings. The operator “like” uses patterns that are described using two

special characters:

zpercent (%). The % character matches any substring.

zunderscore (_). The _ character matches any character.

Find the names of all customers whose street includes the substring

“Main”.

select customer_name

from customer

where customer_street like '% Main%'

Match the name “Main%”

like 'Main\%' escape '\'

SQL supports a variety of string operations such as

zconcatenation (using “||”)

zconverting from upper to lower case (and vice versa)

zfinding string length, extracting substrings, etc.

©Silberschatz, Korth and Sudarshan3.19Database System Concepts, 5th Edition, Oct 5, 2006

Ordering the Display of Tuples

List in alphabetic order the names of all customers having a loan in

Perryridge branch

select distinct customer_name

from borrower, loan

where borrower loan_number = loan.loan_number and

branch_name = 'Perryridge'

order by customer_name

We may specify desc for descending order or asc for ascending

order, for each attribute; ascending order is the default.

zExample: order by customer_name desc

©Silberschatz, Korth and Sudarshan3.20Database System Concepts, 5th Edition, Oct 5, 2006

Duplicates

In relations with duplicates, SQL can define how many copies of tuples

appear in the result.

Multiset versions of some of the relational algebra operators – given

multiset relations r1and r2:

1. σ

(r1):If there are c1copies of tuple t1in r1, and t1satisfies

selections σ

,, then there are c1 copies of t1in σ

(r1).

2. ΠA (r ): For each copy of tuple t1in r1, there is a copy of tuple

ΠA (t1)in ΠA (r1) where ΠA (t1) denotes the projection of the single

tuple t1.

3. r1 x r2:If there are c1copies of tuple t1in r1and c2copies of tuple

t2in r2, there are c1x c2copies of the tuple t1. t2in r1 x r2

©Silberschatz, Korth and Sudarshan3.21Database System Concepts, 5th Edition, Oct 5, 2006

Duplicates (Cont.)

Example: Suppose multiset relations r1(A, B) and r2(C) are as

follows:

r1= {(1, a) (2,a)} r2= {(2), (3), (3)}

Then ΠB(r1) would be {(a), (a)}, while ΠB(r1) x r2would be

{(a,2), (a,2), (a,3), (a,3), (a,3), (a,3)}

SQL duplicate semantics:

select A1,, A2, ..., An

from r1, r2, ..., rm

where P

is equivalent to the multiset version of the expression:

))(( 21,,, 21 mPAAA rrr

n×

∏

©Silberschatz, Korth and Sudarshan3.22Database System Concepts, 5th Edition, Oct 5, 2006

Set Operations

The set operations union, intersect, and except operate on relations

and correspond to the relational algebra operations ∪, ∩, −.

Each of the above operations automatically eliminates duplicates; to

retain all duplicates use the corresponding multiset versions union all,

intersect all and except all.

Suppose a tuple occurs mtimes in rand n times in s, then, it occurs:

zm + n times in r union all s

zmin(m,n) times in rintersect all s

zmax(0, m – n) times in rexcept all s

©Silberschatz, Korth and Sudarshan3.23Database System Concepts, 5th Edition, Oct 5, 2006

Set Operations

Find all customers who have a loan, an account, or both:

(select customer_name from depositor)

except

(select customer_name from borrower)

(select customer_name from depositor)

intersect

(select customer_name from borrower)

Find all customers who have an account but no loan.

(select customer_name from depositor)

union

(select customer_name from borrower)

Find all customers who have both a loan and an account.

©Silberschatz, Korth and Sudarshan3.24Database System Concepts, 5th Edition, Oct 5, 2006

Aggregate Functions

These functions operate on the multiset of values of a column of

a relation, and return a value

avg: average value

min: minimum value

max: maximum value

sum: sum of values

count: number of values

©Silberschatz, Korth and Sudarshan3.25Database System Concepts, 5th Edition, Oct 5, 2006

Aggregate Functions (Cont.)

Find the average account balance at the Perryridge branch.

Find the number of depositors in the bank.

Find the number of tuples in the customer relation.

select avg (balance)

from account

where branch_name = 'Perryridge'

select count (*)

from customer

select count (distinct customer_name)

from depositor

©Silberschatz, Korth and Sudarshan3.26Database System Concepts, 5th Edition, Oct 5, 2006

Aggregate Functions

Aggregate Functions –

–Group By

Group By

Find the number of depositors for each branch.

Note: Attributes in select clause outside of aggregate functions must

appear in group by list

select branch_name, count (distinct customer_name)

from depositor, account

where depositor.account_number = account.account_number

group by branch_name

©Silberschatz, Korth and Sudarshan3.27Database System Concepts, 5th Edition, Oct 5, 2006

Aggregate Functions

Aggregate Functions –

–Having Clause

Having Clause

Find the names of all branches where the average account balance is

more than $1,200.

Note: predicates in the having clause are applied after the

formation of groups whereas predicates in the where

clause are applied before forming groups

select branch_name, avg (balance)

from account

group by branch_name

having avg (balance)> 1200

©Silberschatz, Korth and Sudarshan3.28Database System Concepts, 5th Edition, Oct 5, 2006

Null Values

It is possible for tuples to have a null value, denoted by null, for some

of their attributes

null signifies an unknown value or that a value does not exist.

The predicate is null can be used to check for null values.

zExample: Find all loan number which appear in the loan relation

with null values for amount.

select loan_number

from loan

where amount is null

The result of any arithmetic expression involving null is null

zExample: 5 + null returns null

However, aggregate functions simply ignore nulls

zMore on next slide

©Silberschatz, Korth and Sudarshan3.29Database System Concepts, 5th Edition, Oct 5, 2006

Null Values and Three Valued Logic

Any comparison with null returns unknown

zExample: 5 < null or null <> null or null = null

Three-valued logic using the truth value unknown:

zOR: (unknown or true) = true,

(unknown or false) = unknown

(unknown or unknown) = unknown

zAND: (true and unknown) = unknown,

(false and unknown) = false,

(unknown and unknown) = unknown

zNOT: (not unknown) = unknown

z“Pis unknown” evaluates to true if predicate Pevaluates to

unknown

Result of where clause predicate is treated as false if it evaluates to

unknown

©Silberschatz, Korth and Sudarshan3.30Database System Concepts, 5th Edition, Oct 5, 2006

Null Values and Aggregates

Total all loan amounts

select sum (amount )

from loan

zAbove statement ignores null amounts

zResult is null if there is no non-null amount

All aggregate operations except count(*) ignore tuples with null

values on the aggregated attributes.

©Silberschatz, Korth and Sudarshan3.31Database System Concepts, 5th Edition, Oct 5, 2006

Nested Subqueries

SQL provides a mechanism for the nesting of subqueries.

A subquery is a select-from-where expression that is nested within

another query.

A common use of subqueries is to perform tests for set membership, set

comparisons, and set cardinality.

©Silberschatz, Korth and Sudarshan3.32Database System Concepts, 5th Edition, Oct 5, 2006

Example Query

Find all customers who have both an account and a loan at the bank.

Find all customers who have a loan at the bank but do not have

an account at the bank

select distinct customer_name

from borrower

where customer_name not in (select customer_name

from depositor )

select distinct customer_name

from borrower

where customer_name in (select customer_name

from depositor )

©Silberschatz, Korth and Sudarshan3.33Database System Concepts, 5th Edition, Oct 5, 2006

Example Query

Find all customers who have both an account and a loan at the

Perryridge branch

Note: Above query can be written in a much simpler manner. The

formulation above is simply to illustrate SQL features.

select distinct customer_name

from borrower, loan

where borrower.loan_number = loan.loan_number and

branch_name = 'Perryridge' and

(branch_name, customer_name )in

(select branch_name, customer_name

from depositor, account

where depositor.account_number =

account.account_number )

©Silberschatz, Korth and Sudarshan3.34Database System Concepts, 5th Edition, Oct 5, 2006

Set Comparison

Find all branches that have greater assets than some branch located

in Brooklyn.

Same query using > some clause

select branch_name

from branch

where assets > some

(select assets

from branch

where branch_city = 'Brooklyn')

select distinct T.branch_name

from branch as T, branch as S

where T.assets > S.assets and

S.branch_city = 'Brooklyn'

©Silberschatz, Korth and Sudarshan3.35Database System Concepts, 5th Edition, Oct 5, 2006

Definition of Some Clause

F <comp> some r ⇔ ∃ t ∈

such that (F <comp> t )

Where <comp> can be: <, ≤, >, =, ≠

(5 < some ) = true

) = false

(5 ≠some ) = true (since 0 ≠5)

(read: 5 < some tuple in the relation)

(5 < some

) = true

(5 = some

(= some) ≡in

However, (≠some) ≡not in

©Silberschatz, Korth and Sudarshan3.36Database System Concepts, 5th Edition, Oct 5, 2006

Example Query

Find the names of all branches that have greater assets than all

branches located in Brooklyn.

select branch_name

from branch

where assets > all

(select assets

from branch

where branch_city = 'Brooklyn')

©Silberschatz, Korth and Sudarshan3.37Database System Concepts, 5th Edition, Oct 5, 2006

Definition of all Clause

F <comp> all r ⇔ ∀ t ∈

(F <comp> t)

(5 < all ) = false

) = true

(≠all) ≡not in

However, (= all) ≡in

(5 ≠all ) = true (since 5 ≠4 and 5 ≠6)

(5 < all

) = false

(5 = all

©Silberschatz, Korth and Sudarshan3.38Database System Concepts, 5th Edition, Oct 5, 2006

Test for Empty Relations

The exists construct returns the value true if the argument subquery is

nonempty.

exists r ⇔ r ≠Ø

not exists r ⇔ r = Ø

©Silberschatz, Korth and Sudarshan3.39Database System Concepts, 5th Edition, Oct 5, 2006

Example Query

Find all customers who have an account at all branches located in

Brooklyn.

select distinct S.customer_name

from depositor as S

where not exists (

(select branch_name

from branch

where branch_city = 'Brooklyn')

except

(select R.branch_name

from depositor as T, account as R

where T.account_number = R.account_number and

S.customer_name = T.customer_name ))

Note that X – Y = Ø ⇔X ⊆ Y

Note: Cannot write this query using = all and its variants

©Silberschatz, Korth and Sudarshan3.40Database System Concepts, 5th Edition, Oct 5, 2006

Test for Absence of Duplicate Tuples

The unique construct tests whether a subquery has any duplicate

tuples in its result.

Find all customers who have at most one account at the Perryridge

branch.

select T.customer_name

from depositor as T

where unique (

select R.customer_name

from account, depositor as R

where T.customer_name = R.customer_name and

R.account_number = account.account_number and

account.branch_name = 'Perryridge')

©Silberschatz, Korth and Sudarshan3.41Database System Concepts, 5th Edition, Oct 5, 2006

Example Query

Find all customers who have at least two accounts at the Perryridge

branch.

select distinct T.customer_name

from depositor as T

where not unique (

select R.customer_name

from account, depositor as R

where T.customer_name = R.customer_name and

R.account_number = account.account_number and

account.branch_name = 'Perryridge')

Variable from outer level is known as a correlation variable

©Silberschatz, Korth and Sudarshan3.42Database System Concepts, 5th Edition, Oct 5, 2006

Derived Relations

SQL allows a subquery expression to be used in the from clause

Find the average account balance of those branches where the average

account balance is greater than $1200.

select branch_name, avg_balance

from (select branch_name, avg (balance)

from account

group by branch_name )

as branch_avg ( branch_name, avg_balance )

where avg_balance > 1200

Note that we do not need to use the having clause, since we compute

the temporary (view) relation branch_avg in the from clause, and the

attributes of branch_avg can be used directly in the where clause.

©Silberschatz, Korth and Sudarshan3.43Database System Concepts, 5th Edition, Oct 5, 2006

With Clause

The with clause provides a way of defining a temporary view whose

definition is available only to the query in which the with clause

occurs.

Find all accounts with the maximum balance

with max_balance (value) as

select max (balance)

from account

select account_number

from account, max_balance

where account.balance = max_balance.value

©Silberschatz, Korth and Sudarshan3.44Database System Concepts, 5th Edition, Oct 5, 2006

Complex Queries using With Clause

Find all branches where the total account deposit is greater than the

average of the total account deposits at all branches.

with branch_total (branch_name, value) as

select branch_name, sum (balance)

from account

group by branch_name

with branch_total_avg (value) as

select avg (value)

from branch_total

select branch_name

from branch_total, branch_total_avg

where branch_total.value >= branch_total_avg.value

©Silberschatz, Korth and Sudarshan3.45Database System Concepts, 5th Edition, Oct 5, 2006

Views

In some cases, it is not desirable for all users to see the entire logical

model (that is, all the actual relations stored in the database.)

Consider a person who needs to know a customer’s name, loan number

and branch name, but has no need to see the loan amount. This person

should see a relation described, in SQL, by

(select customer_name, borrower.loan_number, branch_name

from borrower, loan

where borrower.loan_number = loan.loan_number )

A view provides a mechanism to hide certain data from the view of

certain users.

Any relation that is not of the conceptual model but is made visible to a

user as a “virtual relation” is called a view.

View Definition

A view is defined using the create view statement which has the

form

create view v as < query expression >

where <query expression> is any legal SQL expression. The view

name is represented by v.

Once a view is defined, the view name can be used to refer to the

virtual relation that the view generates.

When a view is created, the query expression is stored in the

database; the expression is substituted into queries using the view.

Example Queries

A view consisting of branches and their customers

Find all customers of the Perryridge branch

create view all_customer as

(select branch_name, customer_name

from depositor, account

where depositor.account_number =

account.account_number )

union

(select branch_name, customer_name

from borrower, loan

where borrower.loan_number = loan.loan_number )

select customer_name

from all_customer

where branch_name = 'Perryridge'

Views Defined Using Other Views

One view may be used in the expression defining another view

A view relation v1is said to depend directly on a view relation v2if v2

is used in the expression defining v1

A view relation v1is said to depend on view relation v2if either v1

depends directly to v2 or there is a path of dependencies from v1to

A view relation vis said to be recursive if it depends on itself.

View Expansion

A way to define the meaning of views defined in terms of other views.

Let view v1be defined by an expression e1that may itself contain uses

of view relations.

View expansion of an expression repeats the following replacement

step:

repeat

Find any view relation viin e1

Replace the view relation viby the expression defining vi

until no more view relations are present in e1

As long as the view definitions are not recursive, this loop will

terminate

Modification of the Database

Modification of the Database –

–Deletion

Deletion

Delete all account tuples at the Perryridge branch

delete from account

where branch_name = 'Perryridge'

Delete all accounts at every branch located in the city ‘Needham’.

delete from account

where branch_name in (select branch_name

from branch

where branch_city = 'Needham')

Example Query

Delete the record of all accounts with balances below the average at

the bank.

delete from account

where balance < (select avg (balance )

from account )

zProblem: as we delete tuples from deposit, the average balance

changes

zSolution used in SQL:

1. First, compute avg balance and find all tuples to delete

2. Next, delete all tuples found above (without recomputing avg or

retesting the tuples)

Modification of the Database

Modification of the Database –

–Insertion

Insertion

Add a new tuple to account

insert into account

values ('A-9732', 'Perryridge', 1200)

or equivalently

insert into account (branch_name, balance, account_number)

values ('Perryridge', 1200, 'A-9732')

Add a new tuple to account with balance set to null

insert into account

values ('A-777','Perryridge', null )

Modification of the Database

Modification of the Database –

–Insertion

Insertion

Provide as a gift for all loan customers of the Perryridge branch, a $200

savings account. Let the loan number serve as the account number for the

new savings account

insert into account

select loan_number, branch_name, 200

from loan

where branch_name = 'Perryridge'

insert into depositor

select customer_name, loan_number

from loan, borrower

where branch_name = 'Perryridge'

and loan.account_number = borrower.account_number

The select from where statement is evaluated fully before any of its

results are inserted into the relation (otherwise queries like

insert into table1 select * from table1

would cause problems)

Modification of the Database

Modification of the Database –

–Updates

Updates

Increase all accounts with balances over $10,000 by 6%, all other

accounts receive 5%.

zWrite two update statements:

update account

set balance = balance ∗1.06

where balance > 10000

update account

set balance = balance ∗1.05

where balance ≤10000

zThe order is important

zCan be done better using the case statement (next slide)

Case Statement for Conditional Updates

Same query as before: Increase all accounts with balances over

$10,000 by 6%, all other accounts receive 5%.

update account

set balance = case

when balance <= 10000 then balance *1.05

else balance * 1.06

end

Update of a View

Create a view of all loan data in the loan relation, hiding the amount

attribute

create view loan_branch as

select loan_number, branch_name

from loan

Add a new tuple to branch_loan

insert into branch_loan

values ('L-37‘, 'Perryridge‘)

This insertion must be represented by the insertion of the tuple

('L-37', 'Perryridge', null )

into the loan relation

Updates Through Views (Cont.)

Some updates through views are impossible to translate into

updates on the database relations

zcreate view v as

select loan_number, branch_name, amount

from loan

where branch_name = ‘Perryridge’

insert into vvalues ('L-99','Downtown', '23')

Others cannot be translated uniquely

zinsert into all_customer values ('Perryridge', 'John')

Have to choose loan or account, and

create a new loan/account number!

Most SQL implementations allow updates only on simple views

(without aggregates) defined on a single relation

Joined Relations**

Join operations take two relations and return as a result another

relation.

These additional operations are typically used as subquery

expressions in the from clause

Join condition – defines which tuples in the two relations match, and

what attributes are present in the result of the join.

Join type – defines how tuples in each relation that do not match any

tuple in the other relation (based on the join condition) are treated.

Joined Relations

Joined Relations –

–Datasets for Examples

Datasets for Examples

Relation loan

Relation borrower

Note: borrower information missing for L-260 and loan

information missing for L-155

Joined Relations

Joined Relations –

–Examples

Examples

loan inner join borrower on

loan.loan_number = borrower.loan_number

loan left outer join borrower on

loan.loan_number = borrower.loan_number

Joined Relations

Joined Relations –

–Examples

Examples

loan natural inner join borrower

loan natural right outer join borrower

Joined Relations

Joined Relations –

–Examples

Examples

loan full outer join borrower using (loan_number)

Find all customers who have either an account or a loan (but not both)

at the bank.

select customer_name

from (depositor natural full outer join borrower )

where account_number is null or loan_number is null

Database System Concepts, 5th Ed.

See www.db-book.com for conditions on re-use

End of Chapter 3

Figure 3.1: Database Schema

branch (branch_name, branch_city, assets)

customer (customer_name, customer_street, customer_city)

loan (loan_number, branch_name, amount)

borrower (customer_name, loan_number)

account (account_number, branch_name, balance)

depositor (customer_name, account_number)

Figure 3.3: Tuples inserted into

Figure 3.3: Tuples inserted into loan

loan and

and

borrower

Figure 3.4:

The

The loan

loan and

and borrower

borrower relations

relations